High Resolution Imaging Spectroscopy for Characterizing Soil Properties over Large Areas

Abstract:

Quantitative mapping of high resolution surface soil texture (percentage sand, silt and clay), soil organic matter and chemical constituents are important for understanding infiltration, runoff and other surficial hydrologic processes at different scales. The Visible Near Infrared Analysis (VNIRA) method, which is a combination of imaging spectroscopy and laboratory chemical analysis with an underlying statistical model, has been established for the quantification of soil properties from imaging spectrometer data. In this study we characterize the feasibility of quantifying soil properties over large areas with the aim that these methods may be extended to space-borne sensors such as HyspIRI. Hyperspectral Infrared Imager (HyspIRI) is a space-borne NASA mission concept having 10nm contiguous bands in the VSWIR region (380nm to 2500nm) of the electromagnetic spectra. High resolution (7.6m) Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data collected by NASA immediately after the massive 2011 Mississippi River floods at the Birds Point New Madrid (BPNM) floodway, coupled with in situ samples obtained at the time of the flight, is used to generate HyspIRI like data at 60m resolution. The VNIRA method is applied in a data-mining framework for quantification of the different soil textural properties and chemical constituents. The empirical models are further used for creating quantitative maps of the soil properties for the entire BPNM floodway. These maps are compared with the fine resolution AVIRIS maps of the same area for the different legacy landscape features and spatial correlations with the underlying topography immediately disturbed by the flooding event. The scales of variation in the soil constituents captured by the fine resolution data are also compared to the scales of variation captured by coarser resolution data. This study further explores the issues of applicability, challenges (such as the sensitivity of NDVI from mixed neighborhood pixels and calibration sample sizes on the results) and limitations (field soil sample data collection) of the VNIRA method for determination of soil properties. We expect that the approach can be extended broadly and will lead to the characterization of soil properties that will be benefit a variety of studies.